Note: The job is a remote job and is open to candidates in USA. Upscale AI is building high-performance infrastructure for the next generation of artificial intelligence. The Senior Staff DevOps Engineer will own and scale CI/CD, release workflows, quality gates, build and test infrastructure, observability, and developer processes for AI/HPC Ethernet switching software.
Responsibilities
- Own CI/CD for the ScaleUp stack that powers AI/HPC Ethernet switching (build, unit/integration, gating, artifacts, release promotion)
- Scale pipelines across multi-repo dependencies: switch SDK, SAI adapters, shared test frameworks, and switch simulation / model targets
- Improve build caching, shared runners, and nightlies so large C/C++ and Python SDK builds stay fast and predictable
- Own release / promote workflows (branch policies, artifact publish, pre-gate vs post-gate steps) so SDK drops are repeatable
- Shorten commit → green for teams building programmable data-plane, QoS, ACL, RoCE-era fabrics, and AI-workload traffic patterns
- Add and maintain quality gates: lint, unit tests, model smoke, coverage where useful, overnight soak — high signal, low flake
- Manage artifacts and caches (CI artifacts, object storage as needed) with clear retention and failure handling
- Operate Linux build/test farms for C/C++ SDKs and Python harnesses (toolchains, containers, lab/sim hosts)
- Improve pipeline observability (dashboards, alerts, runbooks, postmortems)
- Secure secrets and access for GitHub Actions, artifact stores, and internal services
- Partner with QA on PR / nightly / soak jobs that validate end-to-end switch behavior before customer and cloud deployments
- Publish reusable pipeline templates so new ScaleUp / AI-networking repos onboard quickly
- Jira: keep engineering work traceable — epics/stories/bugs for CI and infra, link PRs and releases to tickets, support sprint and release planning with SDK/SAI/QA, tighten ticket hygiene (status, components, labels) so blockers and CI debt are visible
Skills
- Strong CI/CD experience (GitHub Actions and/or Jenkins; GitLab CI also fine) in multi-repo environments
- Deep Linux fluency: shells, packaging, toolchains, debugging native builds and shared-library / SDK load paths
- Automation in Python and bash; enough CMake/Make to unblock switch-SDK CI
- Containers (Docker) and self-hosted or cloud runners at meaningful scale
- Proven work reducing flaky tests and improving CI signal-to-noise
- Hands-on Jira (or equivalent): workflows, boards, linking commits/PRs to issues, release/version fields — comfortable driving process with developers, not only “keeping the lights on.”
- Clear communication with hardware-adjacent software teams
- Excitement about AI data centers, Ethernet fabrics, and silicon-software co-design — not only generic cloud DevOps
- Background in networking ASICs, switch SDKs, SAI, DPDK, or NIC/SmartNIC software
- Exposure to AI/ML cluster networking (GPU fabrics, RoCE/RDMA, congestion control, telemetry)
- Simulation / hardware-in-the-loop CI, pytest at scale, junit/Allure-style reporting
- Build-cache and large-monorepo / multi-repo release patterns; backport or branch-gating workflows
- Static analysis / lint gates in CI (e.g. cppcheck, language linters)
- IaC (Terraform/Ansible) and cloud runners (AWS/GCP)
- Atlassian suite beyond Jira (Confluence runbooks, Jira + GitHub automation)
- Release hygiene: versioning, artifacts, SBOM/signing, branch protection / merge gates
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